Bloom's Taxonomy, named after Benjamin Bloom, was the first classification of questions within the education system. In his book, "The Taxonomy of Educational Objectives: The Classification of Educational Goals", he clearly chalks out a plan to design a innovative method to improve the communication between educators on the design of curricula and examinations. The original Bloom's Taxonomy covered the principles of Cognitive domains. Skills in the cognitive domain revolve around knowledge, comprehension, and critical thinking on a particular topic. Bloom divided this into six levels which are Knowledge, Comprehension, Application, Analysis, Synthesis and Evaluation levels.

Our project aims to implement the principles defined in Bloom's Taxonomy to help predict the future scores of student. We apply all the conditions given in the taxonomical specifications. We aim to match all the verbs present in a given question from the given set of verbs specified. Apart from this any other verb which appears in the question is passed through a synonymizer which will generate all different combinations between the synonyms of the verb in contention along with the prescribed set of verbs. Any match, if found, will be added to the set of the given verbs. Thus we also aim to add to the set of the words in the specifications.

Apart from matching of the verbs, we find the cumulative aggregate of the domain score of the question paper. For a given set of marks obtained, we find the total marks obtained by the student for a particular domain. This set of marks is stored into a database. Every time the student logs into the system and adds a new question paper, we extrapolate his set of marks already stored to calculate his new marks. We also provide a visualization as to how he can perform in the next paper that he will be writing and the areas where he can improve. Thus we can predict the future score of a student using Bloom's Taxonomy and hence the name "Predictive Models based on Taxonomy Principles".